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Frontiers in Immunology
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Frontiers in Immunology
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Research.fi
Data Paper . 2020 . Peer-reviewed
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Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

Authors: Basit Jabbar; Shazia Rafique; Outi M. H. Salo-Ahen; Outi M. H. Salo-Ahen; Amjad Ali; Mobeen Munir; Muhammad Idrees; +6 Authors

Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

Abstract

Human papillomavirus (HPV) induced cervical cancer is the second most common cause of death, after breast cancer, in females. Three prophylactic vaccines by Merck Sharp & Dohme (MSD) and GlaxoSmithKline (GSK) have been confirmed to prevent high-risk HPV strains but these vaccines have been shown to be effective only in girls who have not been exposed to HPV previously. The constitutively expressed HPV oncoproteins E6 and E7 are usually used as target antigens for HPV therapeutic vaccines. These early (E) proteins are involved, for example, in maintaining the malignant phenotype of the cells. In this study, we predicted antigenic peptides of HPV types 16 and 18, encoded by E6 and E7 genes, using an immunoinformatics approach. To further evaluate the immunogenic potential of the predicted peptides, we studied their ability to bind to class I major histocompatibility complex (MHC-I) molecules in a computational docking study that was supported by molecular dynamics (MD) simulations and estimation of the free energies of binding of the peptides at the MHC-I binding cleft. Some of the predicted peptides exhibited comparable binding free energies and/or pattern of binding to experimentally verified MHC-I-binding epitopes that we used as references in MD simulations. Such peptides with good predicted affinity may serve as candidate epitopes for the development of therapeutic HPV peptide vaccines.

Keywords

HLA-A, Papillomavirus E7 Proteins, Epitopes, T-Lymphocyte, Uterine Cervical Neoplasms, epitope prediction, T-CELL EPITOPES, 1108 Medical Microbiology, binding affinity, CRYSTAL-STRUCTURE, human papillomavirus, Antigens, Viral, Human papillomavirus 16, Human papillomavirus 18, 3204 Immunology, DNA-Binding Proteins, 1107 Immunology, docking, Vaccines, Subunit, VIRUS, Epitopes, B-Lymphocyte, Female, Life Sciences & Biomedicine, PROTEIN-STRUCTURE, CERVICAL-CANCER, 3101 Biochemistry and cell biology, Immunology, Molecular Dynamics Simulation, 3105 Genetics, MHC-I, peptide vaccine, Humans, Papillomavirus Vaccines, Science & Technology, HUMAN-PAPILLOMAVIRUS TYPE-16, LESIONS, computational, IDENTIFICATION, Histocompatibility Antigens Class I, Papillomavirus Infections, Computational Biology, Oncogene Proteins, Viral, RC581-607, MHC CLASS-I, Repressor Proteins, Structural Homology, Protein, Immunologic diseases. Allergy, Epitope Mapping

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    Top 10%
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
49
Top 10%
Top 10%
Top 10%
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